Question about the use of AGEA

Technical
1

Hi,

I am interested in the AGEA Cluster tool for understanding our experimental data. This viewer with assigned colors to similar gene expression patterns is helpful, but still gives some ambiguities (e.g. red and dark red): which exact cortical subregions are in clusters?

The AGEA bi tree (Fig. 17) which you included in the pdf user guide is useful, but the information is incompleted. Because the figure and its legend did not give sufficient information, the cited papers (M. Sultan, et al 2002; Lydia Ng et al 2009 ) did not contain the referred figure, and many of original links in the guide did not exist any more.

Could you kindly provide the source of the Figure 17? or the information which cortical subregions are assigned to which colors in this AGEA cluster viewer?

Thank you in advance! Looking forward to hearing from you soon!
Best regards,
Yun

2

Hi @YZallen

Just wanted to clarify which figure you are referring to. Is it this one?

image
image1065×777 195 KB

3

Yes. that’s the figure I was referring to.

One additional question to you is “Is the assigned color now different from the earlier version?”
Did I understood correctly? This tree navigation paradigm (Figure 18) was based on the selected voxel in Figure 7.

Below I tried to reproduce the Figure 7. It shows different assigned color?

This is what
![Picture1|683x500](upload://4sCYzsE4sXu41JEHtX4jRLYCVY1.jpeg

Picture1
Picture11384×1012 84.1 KB

Thank you for the helps!
Best regards,
Yun

4

“Is the assigned color now different from the earlier version?”

Yes, there was big change in the data between when the user guide/paper was written to what appears on the website now.

The Nissl CCF was updated to so that it is aligned to the Allen CCFv3. The informatics pipeline was updated so that it would be compatible with the results that was generating with the Developing mouse atlas. And therefore the clustering was also redone and as such you are seeing the color difference between the app and that figure.

We also move from a pdf user guide to an online one (Anatomic Gene Expression Atlas (AGEA) - Allen Mouse Brain Atlas).

We wanted to keep the old user available but it seems like we didn’t clearly mark that it was deprecated. Sorry about the confusion.

5

Thank you very much for the clarification : )

We would like to know which exact cortical subregions are in clusters/assigned to the same color code. Do you have the “new” tree navigation paradigm or the data which are possible to reconstruct the map?

Best regards,
Yun

6

Hi @YZallen , if I understand your question correctly, this json file is what you are looking for: http://api.brain-map.org/api/v2/structure_graph_download/1.json . It describes the structure tree, and contains colour codes (“color_hex_triplet”).

7

Hi, thank you for the link! But I am more confused now…

When using the AGEA cluster and place the seed selector at isocortex, below was the displayed figure. The color code is often layer-specific. For instance, the red-brown color seems to contain SSp-ul1, SSp-II1, MOp1, MOs1, PTLp1, SSp-bfd1, RSPd1, RSPagl1, VISam1 and VISp1.

Picture1
Picture11599×831 51.4 KB

When using the information from the provided link (provided if I understood correctly), one color code (“color-hex-triplet”) includes the entire layers of some cortical subregions. For example, the color code 1F6D5A includes layer 1, 2/3, 5 and 6ab of MO, MOp and MOs.

Are the data (from the provided link) the basis of the AGEA cluster viewer?

Best regards,
Yun

8

I hope that you had a nice Easter holiday.

I would like to follow up my previous question:
I’ve looked closer to the data from the provided link. This does not seems to be the algorithm to your AGEA cluster (possibly for the Reference Altas??), as the data did not have any indication of layer-region correlations which described in Ng et al 2009).

Could you kindly provide the algorithm of the AGEA cluster? Which exact cortical subregions share genomic similarity/are in clusters?

Thank you in advance : )

Best regards,
Yun